Integration of hard and soft supervised machine learning for flood susceptibility mapping.

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第一作者： Soghra,Andaryani

第一单位： Center of Excellence in Hydroinformatics and Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran. Electronic address: s.andaryani@gmail.com.

作者： Soghra,Andaryani ^[1] ; Vahid,Nourani ^[2] ; Ali Torabi,Haghighi ^[3] ; Saskia,Keesstra ^[4]

作者单位： Center of Excellence in Hydroinformatics and Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran. Electronic address: s.andaryani@gmail.com. ^[1] Center of Excellence in Hydroinformatics and Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran; Near East University, Faculty of Civil and Environmental Engineering, Near East Boulevard, 99138, Nicosia, North Cyprus, via Mersin 10, Turkey. ^[2] Water, Energy and Environmental Engineering Research Unit, University of Oulu, 90570, Oulu, Finland. ^[3] Team Soil, Water and Land Use, Wageningen Environmental Research, Droevendaalsesteeg 3, 6708RC, Wageningen, the Netherlands; Civil, Surveying and Environmental Engineering, The University of Newcastle, Callaghan, 2308, Australia. ^[4]

关键词 Ajichay river basin-Iran Artificial neural network Classification Flood susceptibility map Total operating characteristic with area under curve

主题词洪水(Floods);伊朗(Iran);江河(Rivers)

DOI 10.1016/j.jenvman.2021.112731

PMID 33962279

发布时间 2021-05-27

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Journal of environmental management

2021年291卷

112731页

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Integration of hard and soft supervised machine learning for flood susceptibility mapping.

Journal of environmental management

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Integration of hard and soft supervised machine learning for flood susceptibility mapping.

Journal of environmental management

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Journal of environmental management

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